Investigating Cloud–Radiation Error Compensations Stemming From Climate Model Calibration
Abstract
Compensating errors are an obstacle to the development of climate models. We wonder if systematic errors in simulated cloud properties might result from forced error compensation due to targeting top‐of‐atmosphere radiative fluxes in the tuning process while using an inaccurate radiative transfer (RT) parameterization. Here, we investigate the extent to which parametric and structural errors in state‐of‐the‐art RT models might be offset by errors relating to cloud properties, and under what circumstances. For this we run tuning experiments with a Single‐Column version of a climate Model (SCM), with and without a parameterization of 3D radiative effects of clouds, targeting reference solar fluxes calculated on Large‐Eddy Simulation cloud fields. In a first set of tuning experiments, the parameters that control cloud geometry in the radiative transfer code are tuned assuming perfect cloud profiles. Compensation mechanisms are found between cloud geometry effects, notably between cloud vertical overlap and 3D effects. In a second set of experiments, cloud geometry parameters are set to nominal values, and free parameters of the boundary layer and cloud parameterizations are tuned, still targeting radiative metrics. We found that, when 3D effects are neglected in these experiments, reasonable fluxes are obtained only at the expense of overestimated cloud fractions, partly compensating for underestimated cloud reflectivity at low sun. Targeting mean solar‐angle fluxes instead of detailed ones removes this mechanism entirely. This study both enlightens some compensation errors specific to cloud–radiation interaction and illustrates more generally how the tuning tool can be used to study and quantify compensating errors.
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BibTeX
@article{coulondecorzens2026investigating,
title = {{Investigating Cloud–Radiation Error Compensations Stemming From Climate Model Calibration}},
author = {M. Coulon-Decorzens and F. Hourdin and N. Villefranque},
journal = {Journal of Advances in Modeling Earth Systems},
year = {2026},
month = oct,
doi = {10.1029/2025ms005579},
url = {https://hal.science/hal-05826997v1},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Investigating Cloud–Radiation Error Compensations Stemming From Climate Model Calibration
AU - M. Coulon-Decorzens
AU - F. Hourdin
AU - N. Villefranque
PY - 2026
DA - 2026/10/17
JO - Journal of Advances in Modeling Earth Systems
DO - 10.1029/2025ms005579
UR - https://hal.science/hal-05826997v1
AB - Compensating errors are an obstacle to the development of climate models. We wonder if systematic errors in simulated cloud properties might result from forced error compensation due to targeting top‐of‐atmosphere radiative fluxes in the tuning process while using an inaccurate radiative transfer (RT) parameterization. Here, we investigate the extent to which parametric and structural errors in state‐of‐the‐art RT models might be offset by errors relating to cloud properties, and under what circumstances. For this we run tuning experiments with a Single‐Column version of a climate Model (SCM), with and without a parameterization of 3D radiative effects of clouds, targeting reference solar fluxes calculated on Large‐Eddy Simulation cloud fields. In a first set of tuning experiments, the parameters that control cloud geometry in the radiative transfer code are tuned assuming perfect cloud profiles. Compensation mechanisms are found between cloud geometry effects, notably between cloud vertical overlap and 3D effects. In a second set of experiments, cloud geometry parameters are set to nominal values, and free parameters of the boundary layer and cloud parameterizations are tuned, still targeting radiative metrics. We found that, when 3D effects are neglected in these experiments, reasonable fluxes are obtained only at the expense of overestimated cloud fractions, partly compensating for underestimated cloud reflectivity at low sun. Targeting mean solar‐angle fluxes instead of detailed ones removes this mechanism entirely. This study both enlightens some compensation errors specific to cloud–radiation interaction and illustrates more generally how the tuning tool can be used to study and quantify compensating errors.
SN - 1942-2466
ER -